Description
In Spark Connect:
>>> df = spark.sql("values (1, struct('a' as x)), (null, null) as t(a, b)") >>> df.show() +----+----+ | a| b| +----+----+ | 1| {a}| |null|null| +----+----+ >>> df.collect() [Row(a=1, b=Row(x='a')), Row(a=None, b=<Row()>)]
whereas PySpark:
>>> df.collect() [Row(a=1, b=Row(x='a')), Row(a=None, b=None)]